Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method for filtering messages, the method comprising: storing one or more data sets in a memory at a private network, the one or more data sets identifying a plurality of data sources; identifying a data source of an incoming message sent to one or more users of a private network; performing a first analysis on the incoming message that compares the identified data source to the plurality of data sources stored in the memory at the private network, the first analysis resulting in the incoming message being identified as unclassifiable; accessing an external database associated with a trusted community when the incoming message is identified as unclassifiable, wherein the external database is accessed to retrieve a list of one or more allowable message sources; performing a second analysis on the incoming message that compares the identified data source to the list of allowable message sources from the external database, wherein the second analysis results in allowing the incoming message to be delivered to the one or more users of the private network; identifying that an outgoing message from at least one user of the one or more users has been sent to the data source of the incoming message; and updating a first data set of the one or more data sets, the first data set associated with the at least one user, wherein the updated first data set indicates that subsequent incoming messages from the data source are allowed to be delivered to the at least one user without requiring the second analysis.
This invention relates to a message filtering system for private networks, addressing the challenge of securely managing incoming messages from unclassified or unknown sources while maintaining usability. The system stores predefined data sets in a private network memory, which identify trusted data sources. When an incoming message is received, the system first checks its source against the stored data sets. If the source is unclassifiable (i.e., not found in the stored data sets), the system accesses an external database maintained by a trusted community to retrieve a list of allowable message sources. The incoming message is then compared against this external list. If the source is deemed allowable, the message is delivered to the intended users. Additionally, if a user within the private network sends a message to the previously unclassified source, the system updates the local data set to mark that source as trusted for future communications, eliminating the need for repeated external checks. This approach balances security with efficiency by dynamically expanding the trusted source list based on user interactions while initially relying on external validation for unknown sources.
2. The method of claim 1 , further comprising: receiving a second outgoing message from the at least one user and sent to a recipient; and updating the first data set associated with the at least one user to identify the recipient, wherein the updated first data set indicates that incoming messages from the recipient are allowed to be delivered to the at least one user without requiring the second analysis.
This invention relates to a messaging system that dynamically adjusts message filtering based on user interactions. The system addresses the problem of excessive false positives in spam or unwanted message filtering, where legitimate messages from trusted contacts are incorrectly blocked. The invention improves upon prior art by automatically updating user-specific allowlists based on outgoing messages, reducing the need for manual whitelisting. The system operates by first analyzing an outgoing message sent by a user to determine if it is legitimate. If the message is deemed legitimate, the recipient of that message is added to a user-specific data set (allowlist) associated with the user. This data set is then used to bypass further analysis for future incoming messages from the same recipient, ensuring seamless communication with trusted contacts. The system also handles cases where a user sends multiple messages to different recipients, updating the allowlist dynamically to reflect all trusted contacts. The invention enhances user experience by minimizing disruptions in communication while maintaining security. By automating the allowlisting process based on outgoing messages, it reduces administrative overhead and improves the accuracy of message filtering. The system is particularly useful in enterprise environments or high-volume messaging platforms where manual whitelisting is impractical.
3. The method of claim 2 , further comprising sending the second outgoing message to at least the recipient.
A system and method for secure communication involves encrypting messages using a first cryptographic key and transmitting them to a recipient. The recipient decrypts the message using a second cryptographic key derived from the first key. The method further includes sending a second outgoing message to the recipient, which may also be encrypted using the same or a different cryptographic key. The system ensures secure transmission by dynamically generating and managing cryptographic keys, allowing for secure communication between parties. The method may involve additional steps such as key exchange, authentication, and message verification to enhance security. The system is designed to prevent unauthorized access to transmitted messages, addressing the problem of insecure communication channels in digital environments. The method ensures that only authorized recipients can decrypt and access the transmitted messages, maintaining confidentiality and integrity. The system may be implemented in various applications, including messaging apps, email services, and secure file transfer protocols.
4. The method of claim 1 , further comprising: receiving votes from one or more user devices, the votes indicating whether one or more messages sent from a sender are identified as being associated with spam; and calculating a spam probability that the identified sender is associated with spam based on the received votes.
This invention relates to spam detection in messaging systems. The problem addressed is the difficulty of accurately identifying spam messages and senders in real-time, particularly when relying solely on automated filters or limited user feedback. The solution involves a collaborative approach where multiple users can vote on whether messages from a sender are spam, and the system calculates a spam probability for the sender based on these votes. The method includes sending messages from a sender to one or more user devices. Users can then vote on whether the messages are spam. The system collects these votes and calculates a spam probability for the sender by analyzing the voting patterns. This probability can be used to determine whether future messages from the sender should be flagged as spam. The system may also adjust the spam probability over time as more votes are received, improving accuracy. Additionally, the method may include filtering messages based on the calculated spam probability, such as blocking or quarantining messages from high-probability spam senders. The voting mechanism can be integrated into user interfaces, allowing users to easily report spam messages. The system may also provide feedback to users, such as confirming when their votes contribute to blocking a spam sender. This approach enhances spam detection by leveraging collective user input, reducing reliance on imperfect automated filters.
5. The method of claim 4 , further comprising identifying that the identified sender is associated with spam based on the calculated spam probability meeting at least a threshold value.
This invention relates to spam detection in digital communications, specifically identifying spam senders based on calculated spam probabilities. The method involves analyzing communication data to determine whether a sender is associated with spam. A spam probability is calculated for a sender based on various factors, such as message content, sender behavior, or historical data. If the calculated spam probability meets or exceeds a predefined threshold value, the sender is flagged as spam. This process helps filter out unwanted or malicious communications, improving security and user experience in digital messaging systems. The method may also involve additional steps, such as analyzing message metadata, comparing sender attributes to known spam patterns, or applying machine learning models to assess spam likelihood. By dynamically evaluating spam probabilities and applying threshold-based classification, the system effectively identifies and mitigates spam sources.
6. The method of claim 4 , further comprising identifying that the identified sender is not associated with spam based on the calculated spam probability not meeting a threshold value.
A system and method for spam detection in electronic communications analyzes sender behavior to determine whether a message is likely spam. The method involves monitoring communication patterns, such as message frequency, recipient lists, and content characteristics, to generate a spam probability score. If the calculated spam probability does not exceed a predefined threshold, the sender is identified as legitimate, meaning they are not associated with spam. This determination helps filter out unwanted messages while allowing legitimate communications to pass through. The approach may also involve comparing the sender's behavior against known spam patterns or historical data to refine the probability calculation. By dynamically adjusting the threshold based on evolving spam tactics, the system maintains accuracy in distinguishing between spam and non-spam senders. The method ensures that legitimate users are not incorrectly flagged, improving communication reliability and user trust.
7. The method of claim 1 , further comprising: receiving a second incoming message from a sender that is not currently identified in any of the stored data sets; and assigning an initial non-zero value to the sender of the second message based on a policy associated with messages received from senders that are not currently identified in the stored data sets, wherein the non-zero value sets a counter associated with the second incoming message and with at least one of the stored data sets.
This invention relates to message processing systems that evaluate incoming messages based on sender reputation. The problem addressed is the handling of messages from previously unknown senders, where no prior reputation data exists. The system maintains stored data sets containing reputation scores or counters for known senders. When a message is received from an unknown sender, the system assigns an initial non-zero value to that sender based on a predefined policy. This initial value sets a counter associated with the incoming message and links it to at least one of the stored data sets. The counter may be used to track message volume, reputation changes, or other metrics for the new sender. The policy determines how the initial value is calculated, ensuring that unknown senders are not immediately treated as high-risk or low-risk without prior data. This approach allows the system to gradually assess the reputation of new senders while maintaining consistency with existing reputation management processes. The method ensures that messages from unknown sources are processed in a controlled manner, reducing the risk of false positives or negatives in reputation-based filtering.
8. A non-transitory computer-readable storage medium having embodied thereon a program executable by a processor for implementing a method for filtering messages, the method comprising: storing one or more data sets in a memory at a private network, the one or more data sets identifying a plurality of data sources; identifying a data source of an incoming message sent to one or more users of a private network; performing a first analysis on the incoming message that compares the identified data source to the plurality of data sources stored in the memory at the private network, the first analysis resulting in the incoming message being identified as unclassifiable; accessing an external database associated with a trusted community when the incoming message is identified as unclassifiable, wherein the external database is accessed to retrieve a list of one or more allowable message sources; performing a second analysis on the incoming message that compares the identified data source to the list of allowable message sources from the external database, wherein the second analysis results in allowing the incoming message to be delivered to the one or more users of the private network; identifying that an outgoing message from at least one user of the one or more users has been sent to the data source of the incoming message; and updating a first data set of the one or more data sets, the first data set associated with the at least one user, wherein the updated first data set indicates that subsequent incoming messages from the data source are allowed to be delivered to the at least one user without requiring the second analysis.
This invention relates to a message filtering system for private networks, addressing the challenge of securely managing incoming messages from unclassified or untrusted sources. The system stores data sets in a private network memory, identifying approved data sources. When an incoming message is received, the system first checks if its source matches any stored data sources. If the source is unclassifiable, the system accesses an external database maintained by a trusted community to retrieve a list of allowable message sources. A second analysis compares the incoming message's source to this external list. If allowed, the message is delivered to the intended users. Additionally, if a user sends an outgoing message to the source of the incoming message, the system updates the user's data set to automatically allow future messages from that source, bypassing the external database check. This approach enhances security by dynamically expanding trusted sources based on user interactions while maintaining control over message filtering.
9. The non-transitory computer-readable storage medium of claim 8 , further comprising instructions executable to: receive a second outgoing message from the at least one user and sent to a recipient; and update the first data set associated with the at least one user to identify the recipient, wherein the updated first data set indicates that incoming messages from the recipient are allowed to be delivered to the at least one user without requiring the second analysis.
This invention relates to a system for managing message delivery permissions in a communication platform. The problem addressed is the need to efficiently control message delivery between users while minimizing repetitive permission checks. The system involves a non-transitory computer-readable storage medium containing instructions for processing messages. A first data set is maintained for at least one user, storing information about allowed message sources. When an outgoing message is sent by the user to a recipient, the system updates the first data set to include the recipient. This update indicates that future incoming messages from the recipient should be delivered without requiring additional analysis, streamlining the message delivery process. The system also includes instructions for analyzing incoming messages to determine if they should be delivered based on the stored data set. If a message is from a source not in the data set, further analysis is performed to decide whether to deliver it. The invention improves efficiency by reducing redundant permission checks for recurring message exchanges.
10. The non-transitory computer-readable storage medium of claim 9 , further comprising instructions executable to send the second outgoing message to at least the recipient.
A system and method for secure message transmission involves a computing device that processes messages to ensure confidentiality and integrity. The device receives an incoming message, encrypts it using a cryptographic key, and generates a first outgoing message containing the encrypted data. The device then creates a second outgoing message that includes metadata about the first outgoing message, such as a unique identifier or a digital signature, to verify the authenticity and integrity of the first message. The second outgoing message is sent to at least one recipient, ensuring that the recipient can verify the encrypted message's validity before decryption. This approach enhances security by separating the encrypted payload from its metadata, reducing the risk of unauthorized access or tampering. The system may also include additional steps, such as validating the recipient's identity before sending the second outgoing message, further improving security. The method is particularly useful in environments where secure communication is critical, such as financial transactions, healthcare data exchange, or government communications. The use of cryptographic techniques ensures that only authorized parties can access the message content, while the metadata provides a tamper-evident mechanism to detect any unauthorized modifications.
11. The non-transitory computer-readable storage medium of claim 8 , further comprising instructions executable to: receive votes from one or more user devices, the votes indicating whether one or more messages sent from a sender are identified as being associated with spam; and calculate a spam probability that the identified sender is associated with spam based on the received votes.
This invention relates to a system for detecting and classifying spam messages in a communication network. The problem addressed is the identification of spam messages and the determination of whether a sender is likely to be associated with spam based on user feedback. The system involves a non-transitory computer-readable storage medium containing instructions for processing messages and user feedback. The instructions enable the system to receive votes from user devices, where the votes indicate whether messages from a sender are identified as spam. The system then calculates a spam probability for the sender based on the received votes, determining the likelihood that the sender is associated with spam. The system may also include instructions for generating a spam score for each message, where the spam score is based on the spam probability of the sender and other factors such as message content or metadata. Messages with higher spam scores may be flagged as spam or filtered from user inboxes. The system may also update the spam probability of a sender over time as additional votes are received, allowing the system to adapt to changing spam patterns. The invention improves spam detection by incorporating user feedback, reducing false positives, and dynamically adjusting sender reputations based on collective user input. This approach enhances the accuracy and reliability of spam filtering systems.
12. The non-transitory computer-readable storage medium of claim 11 , further comprising instructions executable to identify that the identified sender is associated with spam based on the calculated spam probability meeting at least a threshold value.
This invention relates to spam detection in digital communications, specifically identifying spam messages based on sender behavior. The system analyzes communication patterns to calculate a spam probability for a sender, then determines whether the sender is associated with spam when this probability meets or exceeds a predefined threshold. The spam probability is derived from factors such as message frequency, recipient patterns, and historical spam reports. The system may also track sender reputation scores and compare them against known spam databases. If the calculated probability exceeds the threshold, the sender is flagged as a potential spam source, triggering actions like message filtering or blocking. The invention improves spam detection accuracy by dynamically adjusting thresholds based on evolving sender behavior and reducing false positives by incorporating multiple verification layers. This approach is particularly useful in email, messaging platforms, and other digital communication systems where spam is a persistent issue. The system enhances security by proactively identifying and mitigating spam threats before they reach end users.
13. The non-transitory computer-readable storage medium of claim 11 , further comprising instructions executable to identify that the identified sender is not associated with spam based on the calculated spam probability not meeting a threshold value.
A system and method for spam detection in electronic communications analyzes message content to determine whether a sender is associated with spam. The system processes incoming messages, extracts features from the content, and calculates a spam probability score based on these features. The features may include text patterns, sender reputation data, or other indicators of spam-like behavior. The system compares the calculated spam probability to a predefined threshold value. If the probability does not meet or exceed the threshold, the sender is identified as not associated with spam, allowing the message to be processed or delivered normally. This approach helps reduce false positives in spam detection by ensuring that legitimate messages are not incorrectly flagged as spam. The system may also incorporate additional filtering techniques, such as machine learning models or rule-based checks, to further refine the spam detection process. By dynamically adjusting the threshold or updating the feature set, the system can adapt to evolving spam tactics while maintaining high accuracy in distinguishing legitimate communications from spam.
14. The non-transitory computer-readable storage medium of claim 8 , further comprising instructions executable to: receive a second incoming message from a sender that is not currently identified in any of the stored data sets; and assigning an initial non-zero value to the sender of the second message based on a policy associated with messages received from senders that are not currently identified in the stored data sets, wherein the non-zero value sets a counter associated with the second incoming message and with at least one of the stored data sets.
This invention relates to a system for managing message sender reputation in a communication network. The problem addressed is the handling of messages from unknown or untrusted senders, where initial trust or risk assessment is required to determine how to process incoming messages. The system stores data sets that include sender reputation information, such as trust scores or risk levels, for known senders. When a message is received from a sender not currently identified in the stored data sets, the system assigns an initial non-zero value to that sender based on a predefined policy. This policy determines how to initially classify or score new senders, ensuring that messages from unknown sources are not automatically rejected or fully trusted without evaluation. The assigned non-zero value serves as a counter linked to the incoming message and at least one of the stored data sets. This counter may be used to track message frequency, adjust reputation scores, or apply filtering rules. The system dynamically updates sender reputation data as more messages are received, refining the initial assessment over time. This approach improves security by mitigating risks from unknown senders while allowing for gradual trust establishment.
15. An apparatus for filtering messages, the apparatus comprising: memory at a private network that stores one or more data sets, the one or more data sets identifying a plurality of data sources; a communication interface that receives an incoming message that is identified as being sent from a data source and sent to one or more users of a private network; and a processor that executes instructions stored in the memory, wherein execution of the instructions by the processor: performs a first analysis on the incoming message that compares the identified data source to the plurality of data sources stored in the memory at the private network, the first analysis resulting in the incoming message being identified as unclassifiable; accesses an external database associated with a trusted community when the incoming message is identified as unclassifiable, wherein the external database is accessed to retrieve a list of one or more allowable message sources; performs a second analysis on the incoming message that compares the identified data source to the list of allowable message sources from the external database, wherein the second analysis results in allowing the incoming message to be delivered to the one or more users of the private network; identifies that an outgoing message from at least one user of the one or more users is addressed to the data source of the incoming message; and updates a first data set of the one or more data sets, the first data set associated with the at least one user, wherein the updated first data set indicates that subsequent incoming messages from the data source are allowed to be delivered to the at least one user without requiring the second analysis.
This apparatus filters messages within a private network by verifying the legitimacy of message sources. The system addresses the challenge of determining whether incoming messages from unknown or unclassified sources should be allowed into the private network, balancing security with usability. The apparatus includes memory storing datasets that identify approved data sources, a communication interface for receiving messages, and a processor executing instructions to analyze and filter messages. When an incoming message is identified as unclassifiable based on the stored datasets, the processor accesses an external database associated with a trusted community to retrieve a list of allowable message sources. The message is then compared against this list, and if allowed, it is delivered to the intended users. Additionally, if a user within the private network sends a message to the same data source, the system updates the user's dataset to automatically allow future messages from that source without requiring further external verification. This dynamic updating improves efficiency by reducing redundant checks for previously verified sources while maintaining security. The system ensures that only trusted messages enter the private network, enhancing both security and user experience.
16. The apparatus of claim 15 , wherein the communication interface further receives a second outgoing message from the at least one user; and wherein the processor executes further instructions to: identify a recipient of the second outgoing message; and update the first data set associated with the at least one user to identify the recipient, wherein the updated first data set indicates that incoming messages from the recipient are allowed to be delivered to the at least one user without requiring the second analysis.
This invention relates to a communication system that filters incoming messages based on user preferences and message content. The system addresses the problem of unwanted or spam messages by dynamically adjusting message delivery rules based on user interactions. The apparatus includes a communication interface that receives incoming messages and a processor that analyzes these messages using a first analysis to determine whether they should be delivered to a user. The processor also receives outgoing messages from the user and identifies recipients of these messages. The system then updates a user-specific data set to indicate that future incoming messages from these identified recipients should bypass the first analysis and be delivered directly, streamlining communication for trusted contacts. This approach reduces processing overhead while ensuring that messages from known senders are delivered without unnecessary filtering. The system may also include a user interface for managing message delivery preferences and a storage component for maintaining user-specific data sets. The invention improves communication efficiency by balancing security with user convenience, particularly in environments where message volume is high.
17. The apparatus of claim 16 , wherein the processor executes further instructions to send the second outgoing message to at least the recipient.
A system for secure communication includes a processor that generates a first outgoing message containing a first payload and a first key, and a second outgoing message containing a second payload and a second key. The first key is used to encrypt the second payload, and the second key is used to encrypt the first payload. The processor sends the first outgoing message to a recipient and receives a first incoming message containing a third payload and a third key. The third key is used to decrypt the third payload, and the first key is used to decrypt the third payload. The processor then sends the second outgoing message to the recipient. This system enhances security by using dual encryption keys to protect message payloads, ensuring that each message is encrypted with a unique key that is only decrypted by the corresponding key in the other message. The method prevents unauthorized access to the payloads by requiring both keys to be present for decryption, adding an additional layer of security to the communication process. The system is particularly useful in environments where secure data transmission is critical, such as financial transactions, military communications, or confidential business exchanges.
18. The apparatus of claim 15 , wherein the communication interface further receives votes from one or more user devices, the votes indicating whether one or more messages sent from a sender are identified as being associated with spam, and the processor executes further instructions to calculate a spam probability that the identified sender is associated with spam based on the received votes.
This invention relates to a system for detecting and managing spam messages in a communication network. The problem addressed is the identification of spam messages and senders to improve message filtering and user experience. The apparatus includes a communication interface and a processor. The communication interface receives messages from senders and transmits them to recipient devices. The processor executes instructions to analyze message content and metadata to determine if a message is likely spam. The system also tracks sender behavior and message patterns to identify potential spam sources. The communication interface further receives votes from user devices, where users indicate whether received messages are spam. The processor uses these votes to calculate a spam probability for each sender, quantifying the likelihood that the sender is associated with spam. This probability is used to adjust message filtering rules and prioritize suspicious senders for further review. The system dynamically updates spam detection criteria based on user feedback and evolving spam patterns, improving accuracy over time. The invention enhances spam detection by combining automated analysis with user-reported data, reducing false positives and improving filtering efficiency.
19. The apparatus of claim 18 , wherein the processor executes further instructions to identify that the identified sender is associated with spam based on the calculated spam probability meeting at least a threshold value.
This invention relates to spam detection in electronic communications, specifically identifying spam senders based on calculated spam probabilities. The system processes incoming messages to determine whether the sender is associated with spam. A processor calculates a spam probability for each sender by analyzing message content, sender behavior, and other relevant factors. If the calculated spam probability meets or exceeds a predefined threshold value, the sender is flagged as a spam source. The system may then take automated actions such as filtering, blocking, or flagging messages from that sender. The invention improves spam detection accuracy by dynamically adjusting thresholds and refining probability calculations based on historical data and user feedback. This approach reduces false positives and enhances security by proactively identifying and mitigating spam threats. The system integrates with existing communication platforms to provide real-time spam detection and prevention. The invention is particularly useful in email, messaging, and social media environments where spam is a persistent issue. By leveraging probabilistic analysis, it offers a scalable and adaptive solution to combat evolving spam techniques.
20. The apparatus of claim 15 , wherein the communication interface further receives a second incoming message, and the processor executes further instructions to: identify that a sender of the second message is not currently included in any of the stored data sets; and assign an initial non-zero value to the sender of the second message based on a policy associated with messages received from senders that are not currently included in the stored data sets, wherein the non-zero value sets a counter associated with the second incoming message and with at least one of the stored data sets.
This invention relates to a messaging system that dynamically assigns trust or priority values to message senders based on their inclusion in predefined data sets. The system addresses the challenge of managing incoming messages from unknown or untrusted sources by automatically assigning an initial non-zero value to new senders, which serves as a counter linked to the message and relevant data sets. The apparatus includes a communication interface for receiving messages and a processor that executes instructions to evaluate sender information. When a second incoming message is received from a sender not present in any stored data sets, the system identifies the sender as new and applies a predefined policy to assign an initial non-zero value. This value acts as a counter, associating the message with at least one stored data set, enabling further processing or filtering based on the assigned value. The stored data sets may represent trusted or prioritized senders, and the policy ensures that new senders are initially integrated into the system with a measurable starting point, allowing for gradual trust assessment or prioritization. The system enhances message management by dynamically incorporating new senders while maintaining control over message flow and trust levels.
Unknown
June 30, 2020
Browse 5M+ US patents with plain-English claim translations and AI-generated analysis.